CSC111 Counting Unique Words
--D. Thiebaut (talk) 10:37, 24 April 2014 (EDT)
Counting Unique Words in a Document Using Sets and Lists
# countUniqueWords.py
# D. Thiebaut
# Demonstrates the difference in time complexity between sets and lists.
#
from urllib.request import Request
from urllib.request import urlopen
from time import clock
# getWebPage(): given a URL will go grab the content of the page
# and return it as a string.
def getWebPage( url ):
req = Request( url )
print( "Requesting Web file at", url )
encoding = 'latin-1' # can sometimes be 'utf-8'
text = urlopen( req ).read().decode( encoding )
print( "Done! Received %d characters." % len( text ) )
return text
# countUniqueWordsWithList(): given a string will return
# the number of unique words in the string using a list
# of unique words. The "in" operator is used to check if
# a new word is already in the list or not.
def countUniqueWordsWithList( text ):
words = []
for word in text.lower().split():
word = word.strip()
if word not in words:
words.append( word )
print( "found %d unique words" % len( words ) )
# countUniqueWordsWithSet(): given a string will return
# the number of unique words in the string using a set
# of unique words. The "in" operator is used to check if
# a new word is already in the set or not.
def countUniqueWordsWithSet1( text ):
wordsSet = set( [] )
for word in text.lower().split():
word = word.strip()
wordsSet.add( word )
print( "found %d unique words" % len( wordsSet ) )
def countUniqueWordsWithSet2( text ):
wordsSet = set( text.lower().split() )
print( "found %d unique words" % len( wordsSet ) )
# main(): gets James Joyce's Ulysses from a Web page, and
# measures the time it takes to count the unique words in
# the book using lists, and using sets.
def main():
url = "http://cs.smith.edu/~thiebaut/111b/4300-8.txt"
text = getWebPage( url )
print( "Number of words in document = ", len( text.split() ) )
# count the number of unique words using a set: Method 1
start = clock()
countUniqueWordsWithSet1( text )
end = clock()
print( "elapsed time using a set (Method 1)= %1.3f seconds" % (end-start ) )
# count the number of unique words using a set: Method 2
start = clock()
countUniqueWordsWithSet2( text )
end = clock()
print( "elapsed time using a set (Method 2) = %1.3f seconds" % (end-start ) )
# count the number of unique words using a list
start = clock()
countUniqueWordsWithList( text )
end = clock()
print( "elapsed time using a list = %1.3f seconds" % (end-start ))
main()
Output
Running the code above on a MacBook Pro circa 2011 yields the following execution time:
Requesting Web file at http://cs.smith.edu/~thiebaut/111b/4300-8.txt Done! Received 1573082 characters. Number of words in document = 267980 found 45947 unique words elapsed time using a set (Method 1)= 0.230 seconds found 45947 unique words elapsed time using a set (Method 2) = 0.120 seconds found 45947 unique words elapsed time using a list = 110.810 seconds
We find the 45,957 unique words in James Joyce's Ulysses about a thousand times faster using a set than using a list.
Finding the most frequent words in Joyce's Ulysses using a dictionary
# countUniqueWords.py
# D. Thiebaut
# Demonstrates the difference in time complexity between sets and lists.
#
from urllib.request import Request
from urllib.request import urlopen
from time import clock
# getWebPage(): given a URL will go grab the content of the page
# and return it as a string.
def getWebPage( url ):
req = Request( url )
print( "Requesting Web file at", url )
encoding = 'latin-1' # can sometimes be 'utf-8'
text = urlopen( req ).read().decode( encoding )
print( "Done! Received %d characters." % len( text ) )
return text
# countUniqueWordsWithList(): given a string will return
# the number of unique words in the string using a list
# of unique words. The "in" operator is used to check if
# a new word is already in the list or not.
def countUniqueWordsWithList( text ):
words = []
for word in text.lower().split():
word = word.strip()
if word not in words:
words.append( word )
print( "found %d unique words" % len( words ) )
# countUniqueWordsWithSet(): given a string will return
# the number of unique words in the string using a set
# of unique words. The "in" operator is used to check if
# a new word is already in the set or not.
def countUniqueWordsWithSet1( text ):
wordsSet = set( [] )
for word in text.lower().split():
word = word.strip()
wordsSet.add( word )
print( "found %d unique words" % len( wordsSet ) )
def countUniqueWordsWithSet2( text ):
wordsSet = set( text.lower().split() )
print( "found %d unique words" % len( wordsSet ) )
def countFrequencies( text ):
freq = {}
for word in text.split():
try:
freq[word] += 1
except KeyError:
freq[word] = 1
tuples = [ (count,word) for word,count in freq.items() ]
tuples.sort()
return tuples[-10:]
# main(): gets James Joyce's Ulysses from a Web page, and
# measures the time it takes to count the unique words in
# the book using lists, and using sets.
def main():
url = "http://cs.smith.edu/~thiebaut/111b/4300-8.txt"
text = getWebPage( url )
print( "Number of words in document = %d\n\n" % len( text.split() ) )
# find the most frequent word in the text
start = clock()
tuples = countFrequencies( text )
end = clock()
for count, word in tuples:
print( "most frequent top-10 word \"%5s\" appeared %d times" % (word, count) )
print( "\nelapsed time using a dictionary = %1.3f seconds\n" % (end-start ) )
# count the number of unique words using a set: Method 1
start = clock()
countUniqueWordsWithSet1( text )
end = clock()
print( "elapsed time using a set (Method 1)= %1.3f seconds\n" % (end-start ) )
# count the number of unique words using a set: Method 2
start = clock()
countUniqueWordsWithSet2( text )
end = clock()
print( "elapsed time using a set (Method 2) = %1.3f seconds\n" % (end-start ) )
# count the number of unique words using a list
start = clock()
countUniqueWordsWithList( text )
end = clock()
print( "elapsed time using a list = %1.3f seconds\n" % (end-start ))
main()
